Aggregator
Aggregates tools from multiple MCP servers into a vector database, enabling Large Language Models to efficiently search and utilize a collective set of capabilities.
About
It acts as a central hub for discovering and aggregating tools from various MCP servers, meticulously gathering tool information and storing it within a vector database, leveraging Pinecone for efficient storage and retrieval. By consolidating tool capabilities, it empowers Large Language Models (LLMs) to swiftly search, identify, and orchestrate the execution of a comprehensive range of tools, significantly enhancing the overall performance and utility of the MCP system.
Key Features
- Aggregated Tool Discovery from Multiple MCP Servers
- LLM-Optimized Tool Search and Retrieval
- Cross-Server Tool Orchestration and Invocation
- Vector Database Integration for Tool Metadata (Pinecone)
- 0 GitHub stars
- Enhanced Performance for MCP Systems
Use Cases
- Streamlining the process of tool selection and invocation for automated agents and intelligent systems.
- Providing a centralized gateway for discovering capabilities across multiple distinct MCP servers.
- Empowering Large Language Models to dynamically access and utilize a broad range of tools across a distributed system.